2 PhD Positions to develop a Predictive Framework enabling Real-Time Release Testing in Solid Dosage Manufacturing
This PhD project aims to develop a knowledge-based predictive framework for dissolution testing to enable real-time release testing (RTRt) in solid dosage manufacturing. The research will be conducted in close cooperation with pharmaceutical companies and the UGent research accelerator Centre of Excellence in Sustainable Pharmaceutical Engineering and Manufacturing (CESPE). The research outcome will be published in important scientiﬁc journals.
Traditionally, RTRt frameworks are developed by individual companies and partnering research institutions leading to a costly and resource-intensive process. Moreover, the development requires a thorough process understanding as well as controls embedded in the production processes. In this project, a predictive framework for dissolution testing will be developed using material, process, and PAT data from continuous direct compression process. This project presents a unique opportunity to work at the academia-industry interface on a very important and relevant topic to the pharmaceutical industry. A range of formulations and knowledge from multiple pharmaceutical companies involved in the project will lead to development of a generic and better predictive framework enabling RTRt.
The project currently has two open positions for PhD candidates: a PhD project with an Experimental focus and a PhD project with a mathematical modeling focus. The researcher with an experimental focus will get an in-depth scientific understanding, hands-on experience of direct compression based manufacturing and gain expertise in practical aspects of dissolution test development applicable to an industrial working environment. The researcher with a modeling focus will apply different modeling approaches of developing in vitro predictive dissolution models based on product and process understanding. Hence, a predictive dissolution modeling framework will be developed to support product development within the space explored during formulation and process optimization and as surrogate tests in a regulatory filing towards RTRt.
Experimental research focus:
- Master’s degree in pharmaceutical sciences, physical chemistry, or a related discipline
- Experience in dissolution testing of pharmaceutical dosage forms.
- Experience with various analytical techniques (DSC, XRD, IR, TGA, DVS, HPLC).
- Experience in multivariate data analysis is desirable.
Mathematical modeling research focus:
- Master’s degree in bioengineering, chemical engineering, and process engineering or a related discipline
- Experience with the development of numerical methods
- Experience with mechanistic and data-driven modeling methodologies
- Experience in Python and/or MATLAB is desirable.
- Candidates must have a strong interest in both experiments and theoretical modeling
For further information, please contact:
Pharmaceutical engineering research group (Ghent University) Faculty of Pharmaceutical Sciences
Prof. dr. Ashish Kumar (Ashish.Kumar@UGent.be)
LPPAT research group (Ghent University) Faculty of Pharmaceutical Sciences
Prof. dr. Thomas De Beer (Thomas.DeBeer@UGent.be)
Laboratory of Pharmaceutical Technology (Ghent University) Faculty of Pharmaceutical Sciences
Prof. dr. Chris Vervaet (Chris.Vervaet@UGent.be), Prof. dr. Valérie Vanhoorne (Valerie.Vanhoorne@UGent.be)
How to apply
You have to use the online application tool available here or by sending an email to Ashish.Kumar@UGent.be to provide your CV with names of three references, motivation letter and transcripts of your bachelor and master studies.
Application deadline and start date
The position is available immediately and will remain open until it is filled. While the start date is flexible, the target is to start from Feb 2022.